Unique Uses For Artificial Intelligence

There are a lot of uses for AI in today’s world. Weather forecasting, stock market crashes, drug discovery and more are all examples of how the tech can be used to enhance human capabilities.

But there are some other unique and more unusual applications of AI that have yet to be explored. Let’s take a look at some of them!

Artificial Intelligence

Artificial Intelligence is used to enhance a wide variety of industries and applications. It’s a powerful tool that can help companies save time and improve employee productivity.

AI uses a process called learning to train its models on data, and then it can adapt and learn as new data is available. For example, if a machine wants to play chess, it might look at millions of examples and identify patterns that will guide it in winning the game.

While the fully-realized vision of general AI is still years away, there are some unique uses that are already making a positive impact on people’s lives. These include telemedicine and assisted diagnosis through MRI scanners.

Machine Learning

Machine learning is used in a variety of applications and industries, from chatbots to predictive text. It also powers machines that diagnose medical conditions and autonomous vehicles.

When building a machine learning model, it’s important to choose the right algorithm for your needs. A common type of machine learning is supervised, which uses labeled training sets and data to build a model that can make predictions about the future.

Another is unsupervised, which doesn’t use labels, but instead looks for patterns and intrinsic structures in the data. For example, a machine learning algorithm might look for trends in customers’ default rates on loans.

Deep Learning

Deep learning models use artificial neural networks to learn from large amounts of data. They are used in many applications, including computer vision, speech recognition (NLP), machine translation and robotics.

Streaming platforms have also used deep learning to customize the content that users watch and provide personalized recommendations for shows and movies. They rely on large amounts of data to identify the best content for each user.

One of the most powerful capabilities of deep learning is the ability to colorize images, known as semantic coloring. This process involves taking grayscale images as input, and then producing colorized versions that represent the semantic colors and tones of the input.

Natural Language Processing

Natural Language Processing is a subset of AI that helps computers understand language. The technology has many unique uses, including voice recognition, text translation, and document summarization.

Sentiment analysis, another popular NLP task, is used by businesses to analyze online reviews and social media comments to detect brand sentiment.

This allows them to identify customer pain points, and keep an eye on competitors.

Chatbots are another common NLP application. If a user opens an online business chat, for example, a chatbot will respond with a human-like answer that mimics the question asked by the user.

However, NLP is still in its infancy and is hampered by a number of challenges. For example, the tone of voice can be difficult for an NLP algorithm to pick up when performing speech recognition.


Robots are programmable machines that carry out potentially complex, multi-step processes, often incorporating sensing equipment to identify aspects of their environment.

They may be controlled by humans, an AI system (or a combination of both), or by remote control programming. These devices are often used in industrial applications, but also exist as entertainment and spacecraft.

These robotics are increasingly integrated with AI technologies to make them more intelligent and able to interact with the world around them. They can perform tasks like path finding, autonomous navigation, and self-driving.

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